Aid may become even
more unpredictable, but there are ways to tackle the problem

Low-income countries face many sources of instability. Their economies
are usually dependent on a single primary commodity, making them particularly
vulnerable to climate- or trade-related shocks, and their political systems
are prone to destabilizing regime changes. And even though low-income
countries have few ties with international capital markets—which
can be a source of instability in middle-income countries—they are
still vulnerable to the consequences of volatile financial flows in the
form of aid. Like private capital flows, fluctuations in aid can occur
because of outside changes (for instance, shifts in donor sentiment) or
in response to perceived domestic changes (for instance, in governance
and economic management).

In the years ahead, the volatility of aid flows is likely to increase.
Donors are planning to markedly increase aid and step up coordination
and selectivity of aid recipients to help poor countries reach the UN
Millennium Development Goals by 2015. In addition, donors are shifting
away from project aid to program aid (given in the form of direct budget
or sector support)—and countries will be seeking to underpin long-term
recurrent spending (such as recruiting teachers and increasing the pay
of nurses and doctors) with program aid. This shift will help reduce transaction
costs and drains on limited capacity caused by the need to implement a
large number of projects. But program aid flows tend to be more volatile
than project aid, which is usually committed up front and disbursed on
a multiyear basis.

Thus, the development community runs the risk of slipping into a low-level
equilibrium—that is, countries that budget prudently over the medium
term would discount pledges of assistance; donors would then see fewer
funding gaps, in turn causing aid commitments to fall behind intended
increases or even in absolute terms. Signs of this happening are already
evident, with many low-income countries discounting aid commitments in
their plans. To improve aid predictability, donors must lengthen funding
horizons, and the annual review and programming cycle must be strengthened
at the country level. However, even if progress is made on these fronts,
four major challenges remain:

How can countries deal with residual short-run volatility in disbursements?

Can donors lengthen their commitment horizons without excessive risk
of misallocating aid?

How should levels and trends in performance influence the amounts
allocated to project aid and budget support?

What is the role for results-based aid allocations—as distinct
from policy-based allocations—and how can results-based systems
be improved?

We studied each of these questions to find ways to improve the predictability
of aid, especially aid delivered in the form of budget support. We built
on the existing literature on this topic, which tells us that aid is quite
volatile (Alĕs Bulíř and Javier Hamann, and others estimate that
variability is 30–60 percent of the mean). Volatility is higher
for countries that depend heavily on aid, and program aid tends to be
more volatile than project aid. Commitments are often statistically unhelpful
in predicting disbursements—astonishing given the importance placed
on commitments in medium-term fiscal programs—and despite efforts
to improve predictability, there has not been much progress. A large body
of evidence suggests that the costs of large macroeconomic shocks, including
aid shocks, is high. And anecdotal evidence suggests that efficiency costs
associated with unstable budgetary revenues are large, and that unpredictable
cash limits on spending undermine agreed programs and so weaken ministries’
accountability for results.

Cushioning aid shocks

Given that aid volatility is here to stay, what can countries do to smooth
the impact of short-run fluctuations in disbursements? Reserves represent
the first line of defense for aid-receiving countries, and countries can
adapt reserves and fiscal rules to cushion aid disbursement shocks. But
could countries also develop a parallel mechanism, such as a stabilization
fund—modeled, for instance, on Chile’s copper revenue stabilization
fund—as further protection? To find out, we simulated a simple model,
using a reserve buffer to keep unplanned deviations from aid-financed
spending within 5 percent of target levels. When reserves are plentiful,
the fund operates in "high mode," protecting against downside
shocks. When reserves are below target, the fund operates more cautiously.
One could imagine more sophisticated mechanisms to manage volatility,
but this simple instrument suits our purposes.

Our simulations suggested three main points. First, a reserve tranche
of two to four months of import cover (less than the average level of
five months for countries receiving Poverty Reduction Support Credits
from the World Bank) can smooth expenditures quite effectively under a
range of levels of aid instability. Second, while the simulated reserve
fund does sometimes go "bankrupt," this requires three to
five years of large negative disbursement shocks, giving ample lead time
for donors to organize an emergency response. Third, moderate improvements
in the stability of flows, and a working process to offset negative shocks
with higher flows can greatly ease reserve management strategy.

Lengthening commitment horizons

Multiyear aid commitments are controversial because they run the risk
of over- or under-providing aid in the event of significant changes in
the performance of the recipient country. But are efficiency losses from
suboptimal aid allocations serious enough to discourage multiyear commitments?
How can donors adjust their aid in response to changes in a country’s
performance, while still operating within a multiyear commitment horizon?

We calibrated a simple model of aid allocation on the World Bank’s
Country Policy and Institutional Assessment (CPIA) to assess the trade-off
between optimal allocation and predictability within the framework of
the International Development Association’s (IDA’s) performance-based
allocation system. CPIAs are estimated annually for all World Bank clients,
and the ratings are a major component of the allocation formula. They
are currently available to the public only in the form of quintile rankings
but will be released more fully in 2006. The model (described more fully
in Eifert and Gelb, forthcoming) assumes that the marginal effectiveness
of aid falls as aid increases, and that countries with high CPIA scores
can absorb more aid productively than countries with low scores. Given
countries’ scores during 1999–2003, how large would efficiency
losses from aid misallocation have been if five-year donor programs had
been implemented in 1999? On the upside, how much can commitment rules
reduce aid volatility?

We found, not surprisingly, that risks are larger if countries’
performance scores are volatile. Roughly half of the countries remained
in the same CPIA quintile, with one quarter moving up and the other down.
Most movements were across one quintile, but some countries slipped more
(for example, Côte d’Ivoire and Zimbabwe). We considered three
types of programs. The first, a pure performance-based system, delivered
the optimal quantity of aid to each country in each year. The second,
"pure precommitment," held each country’s aid level
over 2000–2003 at its (optimal) 1999 level. This locks in allocations
to countries with deteriorating performance, thus also preventing the
reallocation of aid to improving countries. The third, "flexible
precommitment," adjusted aid levels if a country’s CPIA score
drifted one-third of a point above or below its 1999 level. This corresponds
to about a 90 percent confidence interval given the likely standard error
of the CPIA score (Gelb, Ngo, and Ye, 2004). This rule would, therefore,
not adjust aid flows unless a country experienced a clearly observable
performance change.

Under the pure performance-based system, allocations have an average
standard deviation of 17 percent of 1999 levels, which is far lower than
estimates of historical volatility. Flexible precommitment is successful
in further reducing volatility, except for the low-rated countries—simulations
show that it can halve variability for countries in the top four performance
quintiles (see Chart 1). For those countries that stay on track throughout
the program, it reduces variability all the way to zero. Of course, where
programs go rapidly off track (as in several of the worst managed countries),
the flexible rule has little stabilizing effect.

Pure precommitment over five years stabilizes flows completely, but is
risky. Efficiency losses (relative to annual optimal allocation) under
this option represent 10.7 percent of aid. But under the flexible rule,
average efficiency losses drop to only 2.3 percent of aid because levels
respond to large changes in performance. Losses are concentrated more
heavily in the more poorly managed countries where absorptive capacity
constraints bind more rapidly. Countries that perform consistently benefit
the most from flexible precommitment.

The results of this exercise argue for using performance-based aid systems
that allow latitude for small changes in ratings—the "typical"
change of +/– 0.1 in a country’s annual CPIA score is within
the range of measurement error. Small changes in scores do not usually
foreshadow subsequent drift in the same direction. Indeed, minor changes
in the survey instrument itself can cause small changes in ratings. There
is little to gain from continually fine-tuning aid levels; identifying
and responding to large changes is more important.

Balancing budget and project support

How much of the total aid given to a country should be channeled through
budget rather than project support? Country circumstances will shape the
answer, but some common principles may apply. The World Bank usually restricts
budget support to stronger performing countries, a practice that has a
better chance of providing stable financing in such cases. How would selectivity
be implemented? It could be formula-based, where countries become eligible
above a certain CPIA performance cutoff, and where the maximum share rises
with performance. A precommitment formula could be adopted to maximize
predictability—subject to adequate performance. If recipient countries
prefer budget support, this provides them with an incentive to bolster
performance. For very high-capacity clients, donors could validate budget
support simply by "certifying" country systems.

However, there may also be a role for budget support in countries whose
budget and financial management systems are still fragile, but where donors
are willing to make an investment as a means to help strengthen them.
This concept of budget support as an investment in country systems suggests
that criteria for budget support should reflect both levels and trends
in performance. How, then, to weight them? Too small a response to trends
might not provide adequate safeguards or incentives to improve. But too
strong a response reduces predictability and undermines the value of budget
support itself. There is no simple answer, especially as it is not easy
to distinguish small, observed trends in performance from measurement
errors.

One approach would be to set a multiyear base level of budget support
and supplement it by incentive payments of up to 10 percent based on interim
"light" assessments of performance. These incentives would
anticipate future performance–driven changes in the aid mix, and
be applied to the following year’s support in order to improve predictability.
Every three years—long enough to expect to identify changes—there
would be a "deep" systematic review of progress in country
systems, supported by independent assessment and comprehensive output
and outcome measurement, including through surveys. This would feed back
into the CPIA and help shape the decision on aid levels and how much to
channel through budget support. Again, major performance changes in the
interim should trigger a comprehensive review.

Improving results-based aid

In recent years, the development community has begun to shift away from
emphasizing only policy prescriptions and actions as a basis for support
to a focus on results, thus creating more room for aid recipients to develop
their own policies. The European Union’s budget support programs
represent the most ambitious move in this direction. They combine a fixed
tranche with a variable tranche that disburses at a level based on the
recipient country’s success in meeting a set of mutually agreed
targets for service delivery (such as immunizations or primary enrollments)
and public financial management. The European Commission recently concluded
that this approach has been quite successful in combining a reasonable
degree of predictability with performance-based incentives. However, it
emphasized that the global community still lacks an analytic framework
to guide the setting of targets.

What is an appropriate three-year target for raising primary enrollment
or vaccination rates? How rapidly can literacy test scores improve or
child mortality decline? Norms for target-setting can be derived in a
number of ways. Clemens (2004) estimates long-run functions to derive
norms for increasing primary enrollment. We use quantile regressions to
relate annualized changes in infant mortality and mortality for children
under five years old to their initial levels. Where mortality rates are
already low, the scope for further gains are limited and changes tend
to be small, but at higher mortality levels country performance diverges.
Some countries have achieved rapid declines in mortality, whereas rates
have stagnated or even risen further in others, generally because high
mortality is a symptom of persistent problems (conflict, poor governance)
or because new challenges are emerging (HIV/AIDS).

Quantile regressions allow us to study this relationship over a range
of percentiles of country performance. With strong efforts, countries
with infant mortality rates above 100 per 1,000 (as is the case in most
of Africa) can reduce mortality at a rate of 2.5–3.5 per 1,000 a
year (this would represent the 75th percentile of experience). For countries
with weak systems and difficult circumstances, median performance may
be a more appropriate target; at the median, infant mortality rates improve
by 1.7–2.3 per 1,000 a year. These estimates might be used to target
rates of improvement for forward-looking programs. Chart 2 illustrates
the estimated "paths" from high to low infant mortality rates
at different percentiles. Over 20 years, the 75th percentile country path
would bring a country from an infant mortality rate of 150 to 100 per
thousand. The 90th percentile country would drop the rate to 80 per thousand.

In sum

Changes in the underlying model of aid away from conditionality and fragmented
projects and toward country leadership supported by more coordinated,
harmonized, and selective donor flows require careful rethinking of how
to design the mechanisms for providing support. Budget support is becoming
an important mechanism, especially for countries with a stronger, and
more consistent, performance record. But it will be important to ensure
that the shift in aid modalities does not replace the problem of uncoordinated
flows with that of coordinated, yet even less stable, support. Our findings
suggest possible approaches.

First, fiscal and reserve management rules can be adapted to cushion
short-term disbursement shocks that are not directly performance-related.
Such a system will work best when there is a clear performance framework
and with mechanisms to convene donors to respond to persistent deviations
of disbursements from commitments. Reserve management and fiscal programming
in low-income countries should thus take into account the objective of
stabilizing spending.

Second, aid can be performance-based with far greater predictability
than in the past. While unconditional multiyear commitment can
be risky, flexible precommitment—where flows are committed several
years ahead and revised only when performance deteriorates or improves
to a substantial degree—appears to be a more attractive option.
Relative to a system of continuously "optimal" allocation,
efficiency losses from this option are modest, and predictability is improved
except for lower-performing countries where aid levels will need to change
in response to large swings in performance. Even without precommitment,
however, flows calibrated by an IDA-type CPIA system are less volatile
than historical aid flows.

Third, some emphasis on performance trends is appropriate,
because budget support can be seen as an investment in country systems
of budget management and service delivery, but the weighting on
these trends cannot be too great as this would destabilize flows
and nullify the gains from support. The weighting suggested here allows
performance trends to be treated as signals of likely future changes in
aid levels, advancing potential gains in the form of incentive payments
without inducing excessive volatility.

Finally, there has been considerable debate on the merits of service
delivery, output, or outcome-based indicators as alternatives to policy-based
indicators, especially for budget support. We do not wish to take sides
in this debate, seeing the two approaches as more complementary than competitive.
But if output-type indicators are to be used, it will be important
to have a reference framework for judging progress. If this is
not done, countries setting more ambitious goals will be penalized relative
to those aiming for more modest improvements. Little research exists so
far on this question, but historical progress can be used in a comparative
framework to construct performance-based norms.